Non-destructive test (NDT) systems play a critical role in maintaining the health and safety of aircraft, power plants, distribution infrastructure, manufacturing operations, and other high value assets. NDT systems are used to provide information that reduces the risk of failure of such assets. For example, NDT systems may be used to determine the condition of a component. Knowing the current damage size in a component may be used to predict future damage size and determine whether the component should be replaced or can remain in service.
For risk analysis using NDT data to be effective, the confidence in information obtained from an NDT system must be ascertained. Thus, NDT systems are qualified by a reliability assessment to determine the confidence level that can be ascribed to the information they provide. One critical element of a reliability assessment is the probability of detection (POD), other elements include, for example, reproducibility. A POD study for an NDT system aims to answer the question “what is the largest damage size the NDT system can miss?”
How to answer this question accurately and efficiently has been a continuing challenge to the NDT community. POD studies generate performance curves that describe the POD as a function of damage size. To perform a POD study, damage standards are created or selected. Each damage standard has one or more inspection locations with damage of known size. A significant number of locations without damage are also utilized. The NDT system response at each inspection location on the damage standards, that is “â” (“a-hat”) data, are recorded in relation to the damage size independently determined for the location, that is “a” or ground truth data. This “â versus a” provides the basis for computing performance curves, the associated parameters, confidence levels and the like.
Because the NDT system response is not completely predictive of the damage size, a maximum likelihood â response as a function of damage size, “a”, is estimated from the â versus a data. This information may also be used to generate POD curves. The variance in the sensor response as a function of “a” may also be computed. Factors contributing to the variance include the repeatability of the inspection procedure, stability of the NDT system, the limitations of characterizing damage by a single “size” metric, and system noise.
MIL-HDBK-1823A, “Nondestructive Evaluation System Reliability Analysis, Apr. 7, 2009, published by the Department of Defense, provides a summary of developing POD studies in general and described the mechanics of some methods for generating performance curves from â versus a data, including the number of damage and no damage sites required.